Identifying AI opportunities in PCB design
Artificial intelligence (AI) continues to confuse even many within technology in part because the term itself is woolly but also because we are only just beginning to clarify its application across different sectors.
A new discussion paper from Siemens aims to provide clarity in the specific area of PCB design. It identifies a number of areas where the introduction of AI techniques such as machine learning, deep learning, natural language processing and computer vision can improve speed, productivity, accuracy and quality.
A consistent theme across the areas the paper identifies is use of the pattern matching capabilities of AI today to improve reuse and more detailed design analysis and thus to build in best practice and thus better quality. It also maintains a close watch on design processes that remain vulnerable to human error.
The key opportunities the paper discusses are:
- Accelerating the learning curve for designers
- Selecting optimal components
- Creating component models
- Analyzing connectivity
- Dynamic reuse of functional blocks
- Applying design constraints
- Optimizing placement and routing
- Analyzing and verifying for fine tuning
- Synthesizing designs
The paper argues that AI can also play an important role in democratizing PCB design, alongside delivering better results for established engineers.
“Key areas for applying AI for PCB design are those that are largely manual or require expert knowledge of electronic systems design tools,” writes author Chandra Akella. “AI enhanced tools empower entry-level users to perform tasks that were traditionally achievable only by experts.”
The paper, Reducing Electronic Systems Design Complexity with AI, is available for download here.
